tests/testthat/_snaps/join.md

In dplyr: A Grammar of Data Manipulation

can't use keep = FALSE with non-equi conditions (#6499)

Code
  left_join(df1, df2, join_by(overlaps(xl, xu, yl, yu)), keep = FALSE)
Condition
  Error in `left_join()`:
  ! Can't set `keep = FALSE` when using an inequality, rolling, or overlap join.

Code
  full_join(df1, df2, join_by(overlaps(xl, xu, yl, yu)), keep = FALSE)
Condition
  Error in `full_join()`:
  ! Can't set `keep = FALSE` when using an inequality, rolling, or overlap join.

join_mutate() validates arguments

Code
  join_mutate(df, df, by = 1, type = "left")
Condition
  Error:
  ! `by` must be a (named) character vector, list, `join_by()` result, or NULL, not the number 1.
Code
  join_mutate(df, df, by = "x", type = "left", suffix = 1)
Condition
  Error:
  ! `suffix` must be a character vector of length 2, not the number 1 of length 1.
Code
  join_mutate(df, df, by = "x", type = "left", na_matches = "foo")
Condition
  Error:
  ! `na_matches` must be one of "na" or "never", not "foo".
Code
  join_mutate(df, df, by = "x", type = "left", keep = 1)
Condition
  Error:
  ! `keep` must be `TRUE`, `FALSE`, or `NULL`, not the number 1.

join_filter() validates arguments

Code
  join_filter(df, df, by = 1, type = "semi")
Condition
  Error:
  ! `by` must be a (named) character vector, list, `join_by()` result, or NULL, not the number 1.
Code
  join_filter(df, df, by = "x", type = "semi", na_matches = "foo")
Condition
  Error:
  ! `na_matches` must be one of "na" or "never", not "foo".

mutating joins trigger many-to-many warning

Code
  out <- left_join(df, df, join_by(x))
Condition
  Warning in `left_join()`:
  Detected an unexpected many-to-many relationship between `x` and `y`.
  i Row 1 of `x` matches multiple rows in `y`.
  i Row 1 of `y` matches multiple rows in `x`.
  i If a many-to-many relationship is expected, set `relationship = "many-to-many"` to silence this warning.

mutating joins compute common columns

Code
  out <- left_join(df1, df2)
Message
  Joining with `by = join_by(x)`

filtering joins compute common columns

Code
  out <- semi_join(df1, df2)
Message
  Joining with `by = join_by(x)`

mutating joins reference original column in y when there are type errors (#6465)

Code
  (expect_error(left_join(x, y, by = join_by(a == b))))
Output
  <error/dplyr_error_join_incompatible_type>
  Error in `left_join()`:
  ! Can't join `x$a` with `y$b` due to incompatible types.
  i `x$a` is a <double>.
  i `y$b` is a <character>.

filtering joins reference original column in y when there are type errors (#6465)

Code
  (expect_error(semi_join(x, y, by = join_by(a == b))))
Output
  <error/dplyr_error_join_incompatible_type>
  Error in `semi_join()`:
  ! Can't join `x$a` with `y$b` due to incompatible types.
  i `x$a` is a <double>.
  i `y$b` is a <character>.

error if passed additional arguments

Code
  inner_join(df1, df2, on = "a")
Condition
  Error in `inner_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  left_join(df1, df2, on = "a")
Condition
  Error in `left_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  right_join(df1, df2, on = "a")
Condition
  Error in `right_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  full_join(df1, df2, on = "a")
Condition
  Error in `full_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  nest_join(df1, df2, on = "a")
Condition
  Error in `nest_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  anti_join(df1, df2, on = "a")
Condition
  Error in `anti_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"
Code
  semi_join(df1, df2, on = "a")
Condition
  Error in `semi_join()`:
  ! `...` must be empty.
  x Problematic argument:
  * on = "a"

nest_join computes common columns

Code
  out <- nest_join(df1, df2)
Message
  Joining with `by = join_by(x)`

nest_join references original column in y when there are type errors (#6465)

Code
  (expect_error(nest_join(x, y, by = join_by(a == b))))
Output
  <error/dplyr_error_join_incompatible_type>
  Error in `nest_join()`:
  ! Can't join `x$a` with `y$b` due to incompatible types.
  i `x$a` is a <double>.
  i `y$b` is a <character>.

validates inputs

Code
  nest_join(df1, df2, by = 1)
Condition
  Error in `nest_join()`:
  ! `by` must be a (named) character vector, list, `join_by()` result, or NULL, not the number 1.
Code
  nest_join(df1, df2, keep = 1)
Condition
  Error in `nest_join()`:
  ! `keep` must be `TRUE`, `FALSE`, or `NULL`, not the number 1.
Code
  nest_join(df1, df2, name = 1)
Condition
  Error in `nest_join()`:
  ! `name` must be a single string, not the number 1.
Code
  nest_join(df1, df2, na_matches = 1)
Condition
  Error in `nest_join()`:
  ! `na_matches` must be a string or character vector.

by = character() technically respects unmatched

Code
  left_join(df1, df2, by = character(), unmatched = "error")
Condition
  Error in `left_join()`:
  ! Each row of `y` must be matched by `x`.
  i Row 1 of `y` was not matched.

by = character() technically respects relationship

Code
  left_join(df, df, by = character(), relationship = "many-to-one")
Condition
  Error in `left_join()`:
  ! Each row in `x` must match at most 1 row in `y`.
  i Row 1 of `x` matches multiple rows in `y`.

by = character() for a cross join is deprecated (#6604)

Code
  out <- left_join(df1, df2, by = character())
Condition
  Warning:
  Using `by = character()` to perform a cross join was deprecated in dplyr 1.1.0.
  i Please use `cross_join()` instead.

Code
  out <- semi_join(df1, df2, by = character())
Condition
  Warning:
  Using `by = character()` to perform a cross join was deprecated in dplyr 1.1.0.
  i Please use `cross_join()` instead.

Code
  out <- nest_join(df1, df2, by = character())
Condition
  Warning:
  Using `by = character()` to perform a cross join was deprecated in dplyr 1.1.0.
  i Please use `cross_join()` instead.

by = named character() for a cross join works

Code
  out <- left_join(df1, df2, by = by)
Condition
  Warning:
  Using `by = character()` to perform a cross join was deprecated in dplyr 1.1.0.
  i Please use `cross_join()` instead.

by = list(x = character(), y = character()) for a cross join is deprecated (#6604)

Code
  out <- left_join(df1, df2, by = list(x = character(), y = character()))
Condition
  Warning:
  Using `by = character()` to perform a cross join was deprecated in dplyr 1.1.0.
  i Please use `cross_join()` instead.

dplyr documentation built on Nov. 17, 2023, 5:08 p.m.